The use of electronic computing devices that provide directions has increased significantly in recent years. Exemplary electronic computing devices that provide directions include navigation systems (e.g., global positioning system (GPS) navigation system). Such devices are widely used to map directions.
Existing methods for integrating search results with mapping for directions are cumbersome and inefficient. For example, it is quite tedious for a user to perform a first search for a starting point, identify a starting point in a first set of search results, perform a second search for an ending point, identify an ending point in a second set of second search results, and then enter the identified starting point and the identified ending point in a mapping application to determine a route between the identified starting point and the identified ending point. This process creates a significant cognitive burden on the user. This process becomes even more tedious if the user wants to select a different search result for the starting point or the ending point. It is well known that people have limited capacity of short-term memory and working memory. (See M. Daneman and P. Carpenter, “Individual differences in working memory and reading Journal of Verbal Learning & Verbal Behavior”, 19(4): 450-66 (1980); G. A. Miller, “The magical number seven, plus or minus two: Some limits on our capacity for processing information”, Psychological Review, 63, 81-97 (1956)). Because of their limited memory capacity, users can easily forget results of previous searches, and thus have to repeat the same searches. Furthermore, users can have difficulty relating results of a previous search with results of a later search. These problems reduce efficiency and productivity. In addition, existing methods take longer than necessary, thereby wasting energy. This latter consideration is particularly important in battery-operated devices.